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Record W2605118486 · doi:10.1061/9780784480502.044

Effects of Balconies on the Wind Loading of a Tall Building

2017· article· en· W2605118486 on OpenAlexaff
T. J. Morton, T. G. Mara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsDillon ConsultingWestern University
Fundersnot available
KeywordsAerodynamicsWind tunnelWind engineeringCladding (metalworking)Structural engineeringEngineeringWind powerWind speedCivil engineeringMarine engineeringGeologyAerospace engineeringMaterials science

Abstract

fetched live from OpenAlex

Balconies are a common architectural feature on mid- and high-rise buildings. The presence of balconies alters the interaction of the wind with the building façade, and thereby the resulting cladding and structural loads. Much of the aerodynamic data which comprise wind loading codes (i.e., ASCE 7, NBCC) are based on prismatic buildings with no external features. This case is generally considered to provide an upper bound, as the aerodynamics of the overall building geometry will be clean and well-correlated with height. With advances in modelling capabilities in previous years, the inclusion of balconies and other minor external features on wind tunnel test models has become more achievable and thus is of interest in determining the final wind loads and responses for the building, as well as determining reductions that may exist from code-specified values. A challenge that exists for wind engineers is that occasionally balconies may be added, removed, or modified as the design of the project progresses (or after the initial wind tunnel test has been performed). This paper discusses the impacts of balconies on the overall wind loads and responses for a unique building to illustrate some of the differences between external geometries with and without balconies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.228
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2017
Admission routes1
Has abstractyes

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